library(tidyverse)
exported_package_author <- read.csv("exported_funs_exts_ggplot2_tidyverse_org.csv")
exported_package_author %>% tibble() %>% distinct()
## # A tibble: 5,415 × 3
## user repo fun_exported
## <chr> <chr> <chr>
## 1 YaoxiangLi ggpca ggpca
## 2 YaoxiangLi ggpca run_app
## 3 thomasp85 ggforce FacetCol
## 4 thomasp85 ggforce FacetGridPaginate
## 5 thomasp85 ggforce FacetMatrix
## 6 thomasp85 ggforce FacetRow
## 7 thomasp85 ggforce FacetStereo
## 8 thomasp85 ggforce FacetWrapPaginate
## 9 thomasp85 ggforce FacetZoom
## 10 thomasp85 ggforce GeomArc
## # ℹ 5,405 more rows
exported_package_author %>%
mutate(fun_prefix = fun_exported %>% str_extract(".*?_")) %>%
remove_missing() %>%
select(repo, fun_prefix) %>%
group_by(fun_prefix) %>%
filter(n() > 20) %>%
filter(repo != "ggforce") %>%
ggedgelist:::ggedgelist_quick(layout = "fr", include_names = T)
## Warning: Removed 1196 rows containing missing values or values outside the
## scale range.

exported_package_author %>%
mutate(fun_prefix = fun_exported %>% str_extract(".*?_")) %>%
mutate(user_repo = paste0(user, "/", repo)) %>%
# filter(n() < 200, .by = user_repo) %>%
# sample_n(500) %>%
select(fun_prefix, fun_exported, user_repo) %>%
filter((fun_prefix %in% c("stat_", "facet_", "geom_", "coord_", "theme_", "scale_"))) %>%
pivot_longer(cols= c(user_repo, fun_prefix)) %>%
select(fun_exported, value) %>%
ggedgelist:::ggedgelist_quick(layout = "fr", include_names = T)
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